Utility analysis of digital villages to empower balanced urban-rural development based on the three-stage DEA-Malmquist model

Cao, Lingling; Niu, Huawei; Wang, Yifeng

doi:10.1371/journal.pone.0270952

Cited by 22 publications

(15 citation statements)

References 24 publications

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“…For example, with respect to indicators, Chao et al evaluated the e-commerce labor, professional skills training, and the number of mobile phones per capita [ 55 ]. Furthermore, Zhang et al selected policy guidance, spatial compactness, and facility convenience as indicators [ 56 ], and Cao et al selected indicators such as digital infrastructure, local finance, the industrial structure, technological innovation, and educational level [ 57 ]. This study utilizes the level of digital village construction as the target layer; it utilizes institutions, human resources, and technology as sub-target layers; and it contains five criteria layers and 17 evaluation indicators.…”

Section: Methodsmentioning

confidence: 99%

Regional unevenness in the construction of digital villages: A case study of China

2023

PLoS ONE

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In regard to the comprehensive promotion of rural revitalization, the construction of digital villages is a crucial development. Because the construction of digital villages is considerably novel, the existing studies mainly focus on the theoretical aspects pertaining to the rational and practical robustness of digital villages, and with regard to regional unevenness, the number of studies that consider the current characteristics, absolute gaps, and impact mechanisms pertaining to the construction of digital villages is insufficient. Based on the regional unevenness that characterizes digital village construction, this study proposes a research framework for digital technology-enabled village construction, which integrates three major factors, namely technology, institutions, and human resources; thus, the comprehensive assessment pertaining to the level of digital village construction is enhanced. This study, which applies the aforementioned research framework, constructs an index system for evaluating the construction level of digital villages, and to reveal the characteristics pertaining to regional heterogeneity and the main influencing factors pertaining to the construction level of digital villages in China (study period; 2015–2020), it utilizes the Dagum Gini coefficient method and the spatial econometric model. Consequently, the researchers observe the following: First, the level of digital village construction in China exhibits a “W-shaped” recovery growth. Second, with respect to the regional level, the eastern region exhibits the highest level of digital village construction, followed by central and western regions; furthermore, we observe that the eastern and western regions account for the greatest intra-regional variation, and that with regard to the overall difference, the inter-regional gap represents the main causative factor. Finally, with regard to influencing factors, technology and innovation capabilities, occupational differentiation of farmers, economic development significantly contribute to the level of digital village construction, whereas fiscal autonomy exerts a significant inhibiting effect. In regard to the level of digital village construction, the research framework and results may provide a novel analytical framework for examining the main sources of regional unevenness, and it may also provide a reference for decision-making, which can influence the construction of digital villages in China as well as in other countries.

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Section: Methodsmentioning

confidence: 99%

Regional unevenness in the construction of digital villages: A case study of China

2023

PLoS ONE

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“…In this study, considering prior studies [7,10,26], we selected nine indicators from the three dimensions of digital infrastructure, industry digitisation, and digital services to constitute an index system for evaluating the level of digital village construction (Table 2). The reasons are as follows: (a) Digital infrastructure is the foundation of digital village construction.…”

Section: Definition Of Variablesmentioning

confidence: 99%

Impact of Digital Village Construction on Agricultural Carbon Emissions: Evidence from Mainland China

Zhang

Feng

Fang

et al. 2023

IJERPH

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Reducing agricultural carbon emissions is required to reach the goal of carbon neutrality and mitigate the effects of climate change. With the advent of the digital economy, we aimed to determine if digital village construction can achieve carbon reduction in agriculture. As such, in this study, we used balanced panel data for 30 provinces in China from 2011 to 2020 to conduct an empirical analysis based on measuring the digital village construction level in each province. We found the following: Firstly, digital village construction is conducive to reducing the carbon emitted from agriculture, and the results of further tests showed that the carbon reduction effect of digital villages is mainly based on the reduction in carbon emissions from chemical fertilisers and pesticides. Secondly, the digital village construction has a stronger inhibiting effect on agricultural carbon emissions in major grain-producing areas than in non-major grain-producing areas. The level of rural human capital is the limiting condition for digital village construction to enable green agricultural development; in areas with higher levels of human capital, digital village construction has a significant inhibiting effect on agricultural carbon emissions. The above conclusions are valuable for the future promotion of digital village construction and the design of a green development model for agriculture.

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“…As shown in Eq. ( 2), denotes the e ciency of health care services in city k in year t. [39][40][41] to reveal its dynamic evolution.…”

Section: Indicatorsmentioning

confidence: 99%

A study of Primary health care service efficiency and its spatial correlation in China

Mei

Kou

et al. 2022

Preprint

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Background China's primary health care system has undergone major changes since the new round of medical reform in 2009, but the current status of primary health care institution service efficiency is still unsatisfactory. The purpose of this study is to compare and evaluate the China’s primary health care institution service efficiency and provide a reference for improving the efficiency and promoting the development of primary health care institution. Methods Based on panel data of 31 provinces (municipalities directly under the central government and autonomous regions) in mainland China from 2011 to 2020, using the super efficiency slack-based measure-data envelopment analysis model, to analyze the data from a static perspective, and the changes in the efficiency of primary health care services were analyzed from a dynamic perspective by using the Malmquist index method. Spatial autocorrelation analysis method was used to verify the spatial correlation of Primary health care service efficiency among various regions. Results The number of Primary health care institutions increased from 918,000 in 2011 to 970,000 in 2020. The average primary health care institution service efficiency in the northeastern region including Jilin (0.324), Heilongjiang (0.460), Liaoning (0.453) and northern regions such as Shaanxi (0.344) and Neimenggu (0.403) was at a low level, while the eastern coastal regions such as Guangdong (1.116), Zhejiang (1.211), Shanghai (1.402) have higher average service efficiency levels. The global Moran's I showed the existence of spatial autocorrelation, and the local Moran's I index suggested that the problem of uneven regional development was prominent, showing a contiguous regional distribution pattern. Among them, H-H (high-efficiency regions) were mainly concentrated in Jiangsu, Anhui and Shanghai, and L-L regions were mostly in northern and northeastern China. Conclusion The service efficiency of primary health care institution in China showed a rising trend in general, but the overall average efficiency was still at a low level, and there were significant geographical differences, which showed a spatial distribution of "high in the east and low in the west, high in the south and low in the north". The northwestern region, after receiving relevant support, has seen a rapid development of primary health care, and its efficiency was steadily improving and gradually reaching a high level. The average primary health care institution service efficiency in the northeastern region including the northern region of China was at a low level, while the average efficiency in the eastern coastal region and some economically developed regions was high, which also verifies the dependence and high symbiosis of primary health care institution service efficiency on regional economy.

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Utility analysis of digital villages to empower balanced urban-rural development based on the three-stage DEA-Malmquist model

Cited by 22 publications

References 24 publications

Regional unevenness in the construction of digital villages: A case study of China

Regional unevenness in the construction of digital villages: A case study of China

Impact of Digital Village Construction on Agricultural Carbon Emissions: Evidence from Mainland China

A study of Primary health care service efficiency and its spatial correlation in China

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